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Stepanov-Like Almost Periodic Dynamics of Clifford-Valued Stochastic Fuzzy Neural Networks with Time-Varying Delays

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Abstract

In this paper, we study the Stepanov-like almost periodic dynamics for a class of Clifford-valued stochastic fuzzy neural networks with time-varying delays. Different from the previous studies, we study p-th Stepanov-like almost periodic solutions in distribution, not in p-th mean. Firstly, we study the existence and uniqueness of p-th Stepanov-like almost periodic solutions in distribution of this kind of neural networks by using Banach fixed point theorem. Then, we investigate the global exponential stability of the unique p-th Stepanov-like almost periodic solution by using inequality techniques and counter proof method. Even if the system we consider is a real-valued one, our results are new. Finally, we give an example to illustrate the feasibility of our results.

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Acknowledgements

The authors would like to thank the Editor and the anonymous referees for their helpful comments and valuable suggestions regarding this article.

Funding

This work is supported by the National Natural Science Foundation of China under Grant No. 11861072 and the Applied Basic Research Foundation of Yunnan Province under Grant No. 2019FB003.

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Author notes

  1. Xiaohui Wang and Bing Li have contributed equally to this work.

Authors and Affiliations

  1. Department of Mathematics, Yunnan University, Kunming, 650091, Yunnan, China

    Yongkun Li & Xiaohui Wang

  2. School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, 650500, Yunnan, China

    Bing Li

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  1. Yongkun Li
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Each of the authors contributed to each part of this study equally, all authors read and approved the final manuscript.

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Correspondence to Yongkun Li.

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Li, Y., Wang, X. & Li, B. Stepanov-Like Almost Periodic Dynamics of Clifford-Valued Stochastic Fuzzy Neural Networks with Time-Varying Delays. Neural Process Lett 54, 4521–4561 (2022). https://doi.org/10.1007/s11063-022-10820-x

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